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Supervised topic models with word order structure for document classification and retrieval learning., , and . Inf. Retr. Journal, 18 (4): 283-330 (2015)An Unsupervised Technical Readability Ranking Model by Building a Conceptual Terrain in LSI., and . SKG, page 39-46. IEEE Computer Society, (2012)D-GloVe: A Feasible Least Squares Model for Estimating Word Embedding Densities., and . COLING, page 1849-1860. ACL, (2016)The Effect of Scientific Collaboration on CSCW Research: A Scientometric Study., , , , and . CSCWD, page 129-134. IEEE, (2019)An unsupervised topic segmentation model incorporating word order., and . SIGIR, page 203-212. ACM, (2013)Jointly Learning Word Embeddings and Latent Topics., , , , and . SIGIR, page 375-384. ACM, (2017)Unsupervised Learning of Distributional Relation Vectors., , and . ACL (1), page 23-33. Association for Computational Linguistics, (2018)An unsupervised technical difficulty ranking model based on conceptual terrain in the latent space., , , and . JCDL, page 351-352. ACM, (2012)Hybrid Machine-Crowd Interaction for Handling Complexity: Steps Toward a Scaffolding Design Framework., , , , and . Macrotask Crowdsourcing, Springer, (2019)Probabilistic Relation Induction in Vector Space Embeddings., , and . CoRR, (2017)